In this paper we propose a novel recommender system which enhances user-based collaborative filtering by using a trust-based social network. Our main idea is to use infinitesimal ...
Context has been recognized as an important factor to consider in personalized Recommender Systems. However, most model-based Collaborative Filtering approaches such as Matrix Fac...
Web-page recommendation is to predict the next request of pages that Web users are potentially interested in when surfing the Web. This technique can guide Web users to find more u...
Matrix factorization (MF) models have proved efficient and well scalable for collaborative filtering (CF) problems. Many researchers also present the probabilistic interpretation o...
This paper proposes a novel, unified, and systematic approach to combine collaborative and content-based filtering for ranking and user preference prediction. The framework inco...